Refining Visual Artifacts in Diffusion Models via Explainable AI-based Flaw Activation Maps

This article, sourced from ArXiv, focuses on improving diffusion models by addressing visual artifacts. It utilizes Explainable AI (XAI) techniques, specifically flaw activation maps, to identify and refine these artifacts. The core idea is to leverage XAI to understand and correct the imperfections in the generated images. The research likely explores how these maps can pinpoint areas of concern and guide the model's refinement process.